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I2R VC @ ImageClef2017: Ensemble of Deep Learnt Features for Lifelog Video Summarization (2017)
Conference Proceeding
Molino, A., Mandal, B., Jie, L., Lim, J., Subbaraju, V., & Chandrasekhar, V. (2017). I2R VC @ ImageClef2017: Ensemble of Deep Learnt Features for Lifelog Video Summarization.

In this paper we describe our approach for the ImageCLEF-lifelog summarization task. A total of ten runs were submitted, which used only visual features, only metadata information, or both. In the first step, a set of relevant frames are drawn from t... Read More about I2R VC @ ImageClef2017: Ensemble of Deep Learnt Features for Lifelog Video Summarization.

Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer (2017)
Conference Proceeding
Butcher, J. B., Rutter, A. V., Wootton, A. J., Day, C. R., & Sulé-Suso, J. (2017). Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer. In Advances in Computational Intelligence Systems (183-190). https://doi.org/10.1007/978-3-319-66939-7_15

Lung cancer is a widespread disease and it is well understood that systematic, non-invasive and early detection of this progressive and life-threatening disorder is of vital importance for patient outcomes. In this work we present a convergence of fa... Read More about Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer.

Lexicase Selection Outperforms Previous Strategies for Incremental Evolution of Virtual Creature Controllers (2017)
Presentation / Conference
(2017, September). Lexicase Selection Outperforms Previous Strategies for Incremental Evolution of Virtual Creature Controllers. Presented at ECAL 2017: 14th European Conference on Artificial Life, Lyon

Evolving robust behaviors for robots has proven to be a challenging problem. Determining how to optimize behavior for a specific instance, while also realizing behaviors that generalize to variations on the problem often requires highly customized al... Read More about Lexicase Selection Outperforms Previous Strategies for Incremental Evolution of Virtual Creature Controllers.

Spontaneous mutation rate is a plastic trait associated with population density across domains of life. (2017)
Journal Article
Aston, E., McBain, A., Knight, C., Krašovec, R., Richards, H., Hatcher, C., …Gifford, D. (2017). Spontaneous mutation rate is a plastic trait associated with population density across domains of life. PLoS Biology, e2002731 - ?. https://doi.org/10.1371/journal.pbio.2002731

Rates of random, spontaneous mutation can vary plastically, dependent upon the environment. Such plasticity affects evolutionary trajectories and may be adaptive. We recently identified an inverse plastic association between mutation rate and populat... Read More about Spontaneous mutation rate is a plastic trait associated with population density across domains of life..

Standard Enabled Model Generator for Genetic Circuit Design (2017)
Presentation / Conference
Myers, C., Wipat, A., Misirli, G., Nguyen, T., & McLaughlin, J. (2017, August). Standard Enabled Model Generator for Genetic Circuit Design. Presented at 9th International Workshop on Bio-Design Automation, Pittsburgh

A Collaborative Artefact Reconstruction Environment (2017)
Conference Proceeding
Woolley, S. I., Ch’ng, E., Hernandez-Munoz, L., Gehlken, E., Collins, T., Nash, D., …Hanes, L. (2017). A Collaborative Artefact Reconstruction Environment. . https://doi.org/10.14236/ewic/HCI2017.53

A novel collaborative artefact reconstruction environment design is presented that is informed by experimental task observation and participatory design. The motivation for the design was to enable collaborative human and computer effort in the recon... Read More about A Collaborative Artefact Reconstruction Environment.

Reporting Statistical Validity and Model Complexity in Machine Learning based Computational Studies (2017)
Book Chapter
(2017). Reporting Statistical Validity and Model Complexity in Machine Learning based Computational Studies. In EASE '17: Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering (EASE'17) (128-133). https://doi.org/10.1145/3084226.3084283

Background:: Statistical validity and model complexity are both important concepts to enhanced understanding and correctness assessment of computational models. However, information about these are often missing from publications applying machine lea... Read More about Reporting Statistical Validity and Model Complexity in Machine Learning based Computational Studies.

A standard-enabled workflow for synthetic biology. (2017)
Journal Article
Mısırlı, G., Nguyen, T., Oberortner, E., Samineni, M., Wipat, A., Zhang, M., …Kuwahara, H. (2017). A standard-enabled workflow for synthetic biology. Transactions, 793 - 803. https://doi.org/10.1042/BST20160347

A synthetic biology workflow is composed of data repositories that provide information about genetic parts, sequence-level design tools to compose these parts into circuits, visualization tools to depict these designs, genetic design tools to select... Read More about A standard-enabled workflow for synthetic biology..

Secure Real-Time Monitoring and Management of Smart Distribution Grid Using Shared Cellular Network (2017)
Journal Article
Fan. (2017). Secure Real-Time Monitoring and Management of Smart Distribution Grid Using Shared Cellular Network. IEEE Wireless Communications, 10-17. https://doi.org/10.1109/MWC.2017.1600252

The electricity production and distribution is facing two major changes. First, the production is shifting from classical energy sources such as coal and nuclear power towards renewable resources such as solar and wind. Secondly, the consumption in t... Read More about Secure Real-Time Monitoring and Management of Smart Distribution Grid Using Shared Cellular Network.

Secure Real-Time Monitoring and Management of Smart Distribution Grid using Shared Cellular Networks (2017)
Journal Article
Fan. (2017). Secure Real-Time Monitoring and Management of Smart Distribution Grid using Shared Cellular Networks. IEEE Wireless Communications, 10-17. https://doi.org/10.1109/MWC.2017.1600252

The electricity production and distribution is facing two major changes. First, the production is shifting from classical energy sources such as coal and nuclear power towards renewable resources such as solar and wind. Secondly, the consumption in t... Read More about Secure Real-Time Monitoring and Management of Smart Distribution Grid using Shared Cellular Networks.

“Deflecting elastic prism” and unidirectional localisation for waves in chiral elastic systems (2017)
Journal Article
Carta, G., Jones, I., Movchan, N., Movchan, A., & Nieves, M. (2017). “Deflecting elastic prism” and unidirectional localisation for waves in chiral elastic systems. Scientific reports, 7, Article 26. https://doi.org/10.1038/s41598-017-00054-6

For the first time, a design of a “deflecting elastic prism” is proposed and implemented for waves in a chiral medium. A novel model of an elastic lattice connected to a non-uniform system of gyroscopic spinners is designed to create a unidirectional... Read More about “Deflecting elastic prism” and unidirectional localisation for waves in chiral elastic systems.

Would wider adoption of reproducible research be beneficial for empirical software engineering research? (2017)
Journal Article
(2017). Would wider adoption of reproducible research be beneficial for empirical software engineering research?. Journal of Intelligent and Fuzzy Systems, 1509-1521. https://doi.org/10.3233/JIFS-169146

Researchers have identified problems with the validity of software engineering research findings. In particular, it is often impossible to reproduce data analyses, due to lack of raw data, or sufficient summary statistics, or undefined analysis proce... Read More about Would wider adoption of reproducible research be beneficial for empirical software engineering research?.

Using Convolutional Neural Network for Edge Detection in Musculoskeletal Ultrasound Images (2016)
Conference Proceeding
Jabbar, S. I., Day, C. R., Heinz, N., & Chadwick, E. K. (2016). Using Convolutional Neural Network for Edge Detection in Musculoskeletal Ultrasound Images. In 2016 International Joint Conference on Neural Networks (IJCNN)

Fast and accurate segmentation of musculoskeletal ultrasound images is an on-going challenge. Two principal factors make this task difficult: firstly, the presence of speckle noise arising from the interference that accompanies all coherent imaging a... Read More about Using Convolutional Neural Network for Edge Detection in Musculoskeletal Ultrasound Images.

Analysis of the dynamics of temporal relationships of neural activities using optical imaging data (2016)
Journal Article
(2016). Analysis of the dynamics of temporal relationships of neural activities using optical imaging data. Journal of Computational Neuroscience, 107-121. https://doi.org/10.1007/s10827-016-0630-8

The temporal relationship between the activities of neurons in biological neural systems is critically important for the correct delivery of the functionality of these systems. Fine measurement of temporal relationships of neural activities using mic... Read More about Analysis of the dynamics of temporal relationships of neural activities using optical imaging data.

Unsupervised home monitoring of Parkinson's disease motor symptoms using body-worn accelerometers (2016)
Journal Article
(2016). Unsupervised home monitoring of Parkinson's disease motor symptoms using body-worn accelerometers. https://doi.org/10.1016/j.parkreldis.2016.09.009

Introduction
Current PD assessment methods have inherent limitations. There is need for an objective method to assist clinical decisions and to facilitate evaluation of treatments. Accelerometers, and analysis using artificial neural networks (ANN),... Read More about Unsupervised home monitoring of Parkinson's disease motor symptoms using body-worn accelerometers.